Machine Learning Engineer II – Autonomous Driving Performance Evaluation

🕒 June 8

🇺🇸 United States – Remote

💵 $172k - $210k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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Logo of May Mobility

May Mobility

51 - 200 employees

Founded 2017

🚘 Automotive

📦 Logistics

🚗 Transport

Automotive • Logistics • Transport

May Mobility is a pioneer in developing autonomous vehicle technology and transportation solutions. They focus on creating safe, reliable, and accessible public transit options by deploying driverless shuttles in urban settings. Their solutions aim to improve urban mobility, reduce traffic congestion, and provide eco-friendly transportation alternatives. With a strong emphasis on pedestrian and passenger safety, May Mobility's technology integrates seamlessly with existing city infrastructure to offer a new vision of public transportation.

📋 Description

• Design, implement and own ML metrics and evaluation pipelines spanning offline model evaluation, simulation and on-road performance. • Build and maintain test, regression and hillclimbing suites that gate model and stack releases, including automated triage of regressions to root cause. • Drive model improvement through loss analysis, error mining, and data balancing/curation strategies for training and evaluation sets.

🎯 Requirements

• Bachelor's or Master's degree in Robotics, Computer Science, Statistics, or a related field with strong mathematical and engineering foundations. • A minimum of 2 years building evaluation, metrics, or data analysis systems for ML in production. • Proficiency in Python (NumPy/Pandas or equivalent dataframe tooling) with experience in Linux environments. • Familiarity with basic concepts in Machine Learning (losses, train/eval splits, common failure modes) and basic Perception and Planning concepts in Autonomous Driving. • Proficiency in Go or C++ (desirable). • Familiarity with experiment tracking and evaluation tooling such as MLflow, Weights & Biases, or in-house equivalents (desirable). • Familiarity with statistical methods for A/B comparison, regression detection and noisy-metric analysis (desirable). • Familiarity with data mining and curation at scale (embedding-based retrieval, active learning, auto-labeling) (desirable). • Familiarity with visualization and dashboarding tools (Plotly, Grafana, Streamlit or similar) (desirable).

🏖️ Benefits

• Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. • Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available. • Rich retirement benefits, including an immediately vested employer safe harbor match. • Generous paid parental leave as well as a phased return to work. • Flexible vacation policy in addition to paid company holidays. • Total Wellness Program providing numerous resources for overall wellbeing

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